1. Field of the Invention
The present invention relates to character recognition, and more particularly to a method for recognizing characters included in an image photographed by a camera and translating the recognized characters in connection with a dictionary.
2. Description of the Related Art
Conventional character recognition usually involves a method in which the contents of a paper document are scanned by a scanner and the form of the scanned contents is then changed to that of a text file or an electronic document. However, a method has recently been proposed for recognizing characters in an image photographed by a portable digital device that includes a small digital camera mounted thereon.
Conventional scanners are limited to recognizing characters written on paper. On the other hand, a portable digital device, on which a digital camera is mounted, is capable of Optical Character Recognition (OCR) using the camera. Namely, a character recognition method using a camera mounted on a portable digital device can recognize characters represented on each of various mediums (e.g., a monument, a road guide signboard, a menu board, and various explanatory notes).
However, in using the camera for character recognition, as described above, there is no limitation on characters to be recognized. Accordingly, there may occur a case where it is impossible to recognize characters due to not only the diversity of the characters to be recognized but also external factors (e.g., lighting around the characters to be recognized).
FIG. 1 is a flowchart showing a character recognition method for recognizing characters in a photographed image according to the prior art. Referring to FIG. 1, the conventional character recognition method 100 includes photographing an image including characters by a camera in step S1, processing data of the photographed image in step S2, an interface step S3, normalizing each of the characters in step S4, extracting a feature of each normalized character in step S5, recognizing a character and a word based on the extracted feature of each character in step S6, and providing a translation result in step S7.
More specifically, step S1 includes the characters to be recognized, and obtaining an image representing the subject. Step S2 corresponds to converting the photographed image to a gray scale image. The photographed image may be a color image including various colors. However, for character recognition, it is necessary to remove unnecessary colors from the photographed image and convert the photographed image to a gray scale image.
Step S3 corresponds to compensating for the photographed image in order to have a form suitable for the character recognition according to both the characteristics of the camera used for photographing the image and an environment where the image has been photographed.
Also, step S4 corresponds to converting each character (e.g. a consonant and vowel in Hangeul and each letter in the English alphabet, on a minimum basis) to be recognized, which is included in the photographed image, to a character having the form of a predetermined standard. Step S5 corresponds to extracting a feature of each character to be recognized.
Step S6 corresponds to recognizing an objective character (i.e., defining a photographed character) based on the feature of each extracted character. Step S7 corresponds to combining the recognized characters into words and providing the combination result to the user.
The conventional method further includes a user interface step, in which stored result data of recognized characters from step S6 is stored inside of the device, the recognized characters or words are output on a screen device, and then the words selected by a user's selecting means are searched in connection with an electronic DataBase (DB) and are output again on the screen.
In the conventional character recognition method described above, particularly, with respect to recognition and dictionary translation of a character image, a user interface capable of recognizing both characters included in a character image and actually recognized characters is cumbersome. During recognition on the entire character image, the recognition ratio is typically low due to restrictive hardware performance and inclusion of various noises, and herein, a user interface also may be cumbersome.